Sensitivity analysis of queueing models based on polynomial chaos approach
DOI10.1007/S40065-021-00344-YzbMath1475.90017OpenAlexW3203267013MaRDI QIDQ2053746
Lahcene Bachioua, Lounes Ameur
Publication date: 30 November 2021
Published in: Arabian Journal of Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s40065-021-00344-y
Computational methods in Markov chains (60J22) Monte Carlo methods (65C05) Queueing theory (aspects of probability theory) (60K25) Queues and service in operations research (90B22) Applications of Markov renewal processes (reliability, queueing networks, etc.) (60K20) Probabilistic methods in extremal combinatorics, including polynomial methods (combinatorial Nullstellensatz, etc.) (05D40)
Cites Work
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- Sparse polynomial chaos expansions and adaptive stochastic finite elements using a regression approach
- Nonlinear sensitivity analysis of multiparameter model systems
- Making best use of model evaluations to compute sensitivity indices
- Modeling uncertainty in flow simulations via generalized polynomial chaos.
- Stochastic finite element: a non intrusive approach by regression
- The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations
- Sensitivity Analysis in Practice
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